Methods and apparatuses to facilitate strain measurement in textiles

ABSTRACT

An example system to measure strain in an article includes a camera, a processor, and memory. The camera is to capture a plurality of images of the article. The processor and the memory are in selective communication with the camera. The processor and the memory are configured to determine strain in a region of the article based on a plurality of reference marks shown in the plurality of images.

FIELD OF THE DISCLOSURE

Embodiments of the present disclosure generally relate to producing apparel and, more particularly, to methods and apparatuses to facilitate strain measurement in textiles.

BACKGROUND

In recent years, apparel has been developed to support athletes' bodies and to improve athletes' performance. For example, athletic shoes now often include elastomers. The elastomers work to cover, compress, and cushion athletes' feet.

Certain known elastomers are in textile form. When an athlete wears a shoe constructed of these elastomeric textiles, the elastomeric textiles conform to the athlete's foot. The elastomeric textiles further gently squeeze the athlete's foot to provide support to the foot. When the foot flexes, the elastomeric textiles flex with the foot.

However, these known elastomeric textiles are produced in a single, uniform layer. Thus, these known elastomeric textiles have a uniform spring rate and provide undifferentiated compression across the athlete's foot.

Therefore, a need exists for an elastomer that has varying spring rates to provide customized varying levels of compression and resiliency to athletes.

SUMMARY

In one aspect, an example system to measure strain in an article is disclosed that includes a camera, a processor, and memory. The camera is to capture a plurality of images of the article. The processor and the memory are in selective communication with the camera. The processor and the memory are configured to determine strain in a region of the article based on a plurality of reference marks shown in the plurality of images.

In another aspect, an example method to measure strain in an article is disclosed that includes capturing, with a camera, a plurality of images of the article and determining, with a processor, strain in a region of the article based on a plurality of reference marks shown in the plurality of images.

In yet another aspect, an example non-transitory computer readable medium is disclosed that includes instructions that, when executed by a processor, cause the processor to determine strain in a region of an article based on a plurality of reference marks shown in a plurality of images.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an overhead schematic view of an example system to produce variably resilient elastomers according to an embodiment of the present disclosure;

FIG. 2 is a side schematic view of the example system of FIG. 1;

FIG. 3 is a block diagram of an example controller of the example system of FIGS. 1 and 2;

FIG. 4 is a side view of an example shoe utilized with the example system of FIGS. 1 and 2;

FIG. 4A is an example calibration image captured by the example system of FIGS. 1 and 2

FIG. 5 is an example first image captured by the example system of FIGS. 1 and 2;

FIG. 6 is an example second image captured by the example system of FIGS. 1 and 2;

FIG. 7 is an example reinforcement map generated by the example system of FIGS. 1 and 2;

FIG. 8 illustrates a first example upper and an example tongue produced by the example system of FIGS. 1 and 2;

FIG. 9 illustrates a look-up table stored in a memory of the example controller of FIG. 3;

FIG. 10 is a flowchart representative of an example method that may be performed to produce variably resilient elastomers;

FIG. 11 is a side view of an example customized shoe produced using the example system of FIGS. 1 and 2;

FIG. 12 illustrates a second example upper produced by the example system of FIGS. 1 and 2;

FIG. 13 illustrates a third example upper produced by the example system of FIGS. 1 and 2;

FIG. 14 illustrates a fourth example upper produced by the example system of FIGS. 1 and 2;

FIG. 15 illustrates a fifth example upper produced by the example system of FIGS. 1 and 2;

FIG. 16 illustrates a sixth example upper produced by the example system of FIGS. 1 and 2; and

FIG. 17 illustrates a seventh example upper produced by the example system of FIGS. 1 and 2.

Before the embodiments of the disclosure are explained in detail, it is to be understood that the disclosure is not limited in its application to the details of construction and the arrangement of the components set forth in the following description or illustrated in the drawings. The disclosure is capable of other embodiments and of being practiced or being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein are for the purpose of description and should not be regarded as limiting. The use of “including” and “comprising” and variations thereof is meant to encompass the items listed thereafter and equivalents thereof as well as additional items and equivalents thereof.

DETAILED DESCRIPTION

Embodiments of the present disclosure provide an example system that has features to facilitate producing an elastomer that has varying spring rates to provide customized varying levels of compression and resiliency. The example system includes cameras and a controller to measure deformation of an athlete's shoes when the athlete's feet exert forces on the shoes through movement (e.g., running, jumping, kicking, etc.). The controller generates a map of the deformation measurements. The map is provided to a 3D printer of the system, which selectively applies elastomer to shoe components according to the map. Thus, the shoe components are reinforced by the elastomer in a pattern that is customized to the athlete's feet. It should be understood that the system may be used in any type of application to measure deformation in a test article, generate a map, and reinforce components according to the map to produce a stiffened and/or customized article (e.g., clothing, structures, tools, machinery, etc.).

A system 100, according to an embodiment of the present disclosure is depicted in FIGS. 1 and 2. With reference to FIGS. 1 and 2, the system 100 includes a track 106, one or more cameras 110, a controller 114, and a 3D printer 118. In some embodiments, the track 106 and the cameras 110 are located at a testing facility 120 (e.g., a track, a gymnasium, a stadium, a retail location, etc.). In some embodiments, the controller 114 and/or the 3D printer 118 are also located at the testing facility 120. In some embodiments, the controller 114 and/or the 3D printer 118 are located remotely from the track 106 and the cameras 110. As an athlete 122 wearing reference shoes 124 moves along the track 106, the cameras 110 capture image data of the reference shoes 124, which is transmitted to the controller 114. The controller 114 analyzes the image data and instructs the 3D printer 118 to produce shoe components with varying levels of compression and resiliency that are customized to the athlete 122.

With reference to FIGS. 1 and 2, in some instances, the athlete 122 may arrive at the testing facility 120 and be asked to move along the track 106 while wearing the reference shoes 124. More specifically, as the athlete 122 moves along the track 106, the athlete's 120 feet move within and relative to the reference shoes 124 (e.g., sliding, rolling, pronating, laterally, axially, etc.). Thus, the athlete's 120 feet exert forces on the reference shoes 124 to at least momentarily stretch and/or compress parts and/or regions of the reference shoes 124. This stretching and/or compression exerted on the reference shoes 124 may be measured as strain e, a change in length of an article as compared to the original length of the article, as will be explained in greater detail below. By capturing image data of the reference shoes 124 with the cameras 110 from multiple angles, the strain e values experienced across the various regions of the reference shoes 124 may be determined. Using these determined strain e values, a custom pair of shoes with regions having varying levels of reinforcement and/or elasticity may be produced for the athlete 122, as will be explained in greater detail below.

With references to FIGS. 1 and 2, the athlete 122 is shown at a first time t₁ (in phantom) and at a second time t₂. The second time t₂ is after the first time t₁. It should be understood that the time period between t₁ and t₂ is relatively short (e.g., in a range between 0.4 millisecond and 5 milliseconds). Thus, the athlete 122 moves a relatively small distance along the track 106 during the time period between t₁ and t₂.

With reference to FIGS. 1 and 2, in some embodiments, the track 106 is a substrate (e.g., a mat, a carpet, an artificial turf section, etc.) placed on the ground. In some embodiments, the track 106 is a predetermined area outlined on the ground (e.g., with paint, chalk, tape, etc.). In some embodiments, the track 106 is an elongated area between the cameras 110 for the athlete 122 to move and/or run along. In some embodiments, the track 106 is curvilinear. In some embodiments, the track 106 includes one or more corners (not shown).

With reference to FIG. 1 each camera 110 includes one or more lenses 126, a processor 128, and a memory 130. Thus, in some embodiments, one or more of the cameras 110 is a stereoscopic camera. Further, in some embodiments, two single-lensed cameras 110 may be coupled together and/or arranged directly next to one another to produce a stereoscopic (e.g., 3D and/or three dimensional) image. The cameras 110 are arranged about the track 106 to collect image data from multiple views of the reference shoes 124 and the athlete 122. More specifically, the cameras 110 are located at opposing ends and alongside opposing sides of the track 106. Thus, the cameras 110 are located in front of, behind, and to the sides of the athlete 122. With reference to FIG. 2, the cameras 102 are disposed low to the ground along the track 106 to capture image data of the reference shoes 124. It should be understood that the cameras 110 may be alternatively arranged to capture image data of any part and/or side of the athlete 122.

With reference to FIG. 1, the controller 114 is in communication with the cameras 110 and with the 3D printer 118. It should be understood that arrows indicating communication are omitted from FIG. 2 for clarity. The controller 114 includes a processor 132 and a memory 134. More specifically, the controller 114 may be in communication with the cameras 110 and with the 3D printer 118 via direct wired connections, a wired network, wirelessly, a wireless network, etc. Further, the controller 114 may be in selective communication with the cameras 110 and with the 3D printer 118. In other words, the controller 114 may be communicatively connected to the cameras 110 to receive image data and to the 3D printer 118 to transmit 3D printing instructions. Thus, in some embodiments, the controller 114 is remote from the cameras 110 and/or the 3D printer 118.

With reference to FIG. 1, in some embodiments, the controller 114 is a programmable logic controller (PLC). Additionally, the processors 128, 132 may be any suitable processing device or set of processing devices such as, but not limited to, a microprocessor, a microcontroller-based platform, an integrated circuit, one or more field programmable gate arrays (FPGAs), and/or one or more application-specific integrated circuits (ASICs). The memories 130, 134 may be volatile memory (e.g., RAM including non-volatile RAM, magnetic RAM, ferroelectric RAM, etc.), non-volatile memory (e.g., disk memory, FLASH memory, EPROMs, EEPROMs, memristor-based non-volatile solid-state memory, etc.), unalterable memory (e.g., EPROMs), read-only memory, and/or high-capacity storage devices (e.g., hard drives, solid state drives, etc.). In some examples, the memories 130, 134 includes multiple kinds of memory, particularly volatile memory and non-volatile memory.

The memories 130, 134 are computer readable media on which one or more sets of instructions, such as the software for operating the methods of the present disclosure, can be embedded. The instructions may embody one or more of the methods or logic as described herein. For example, the instructions reside completely, or at least partially, within any one or more of the memories 130, 134, the computer readable medium, and/or within the processors 128, 132 during execution of the instructions.

The terms “non-transitory computer-readable medium” and “computer-readable medium” include a single medium or multiple media, such as a centralized or distributed database, and/or associated caches and servers that store one or more sets of instructions. Further, the terms “non-transitory computer-readable medium” and “computer-readable medium” include any tangible medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor or that cause a system to perform any one or more of the methods or operations disclosed herein. As used herein, the term “computer readable medium” is expressly defined to include any type of computer readable storage device and/or storage disk and to exclude propagating signals.

With reference to FIGS. 1 and 2, the 3D printer 118 is an additive manufacturing device. Additive manufacturing is also often referred to as 3D-printing. Products made via additive manufacturing are often referred to as additively manufactured and/or 3D-printed. As used herein, the terms “additive manufacturing,” “3D-printing,” “3D printing,” and the like are equivalent to one another. The 3D printer 118 is configured to extrude and/or deposit subsequent layers of polymers and/or elastomers (e.g., plastic, silicone, artificial rubber, etc.) to produce a predetermined shape. The predetermined shape is provided by the controller 114.

With reference to FIG. 3, the processor 132 is structured to include an image receiver 140, a reference detector 142, a distance determiner 144, a distance comparator 146, a strain determiner 148, and a map compiler 150. The memory 134 stores reinforcement data 152.

With reference to FIG. 4, the reference shoe 124 includes an upper 154, a tongue 156, a sole 158, and laces 160. The upper 154 includes a lateral section 162, a front section 164, and a rear section 166. With reference to FIG. 1, the upper 154 also includes a medial section 168 (shown via the left reference shoe 124 of the athlete 122). Returning to FIG. 4, the front section 164 is opposite the rear section 166. The lateral section 162 is opposite the medial section 168 (shown in FIG. 1). Additionally, the upper 154 features a plurality of reference marks 170. In some embodiments, the plurality of reference marks 170 are arranged in a decorative pattern. In some embodiments, the plurality of reference marks 170 are spread randomly across the reference shoe 124. In some embodiments, the upper 154 is a substrate and the plurality of reference marks 170 are attached to the upper 154 (e.g., printed, embroidered, adhered, fastened, etc.) In some embodiments, the plurality of reference marks 170 are a pattern within the upper 154 (e.g., woven, knitted, crocheted, etc.).

With reference to FIG. 4A, a calibration image 172 taken by the cameras 110 shows the reference shoe 124 under no load and/or constraint. The calibration image 172 is taken at a calibration time t₀. In some instances, the calibration time t₀ is before the first time t₁. In some instances, the calibration time t₀ is after the first time t₁. In some instances, the calibration time t₀ is after the second time t₂. In the illustrated example of FIG. 4A, the calibration image 172 is primarily directed to the lateral section 162. In some instances, the calibration image 172 is a stereoscopic image.

With reference to FIG. 5, a first image 174 taken by the cameras 110 shows the reference shoe 124 at the first time t₁. In the illustrated example of FIG. 5, the first image 174 is primarily directed to the lateral section 162. In some instances, the first image 174 is a stereoscopic image. Similarly, with reference to FIG. 6, a second image 176 taken by the cameras 110 shows the reference shoe 124 at the second time t₂. In the illustrated example of FIG. 6, the second image 176 is also primarily directed to the lateral section 162. In some instances, the second image 176 is a stereoscopic image. As will be explained in greater detail below, the calibration image 172, the first image 174 and/or the second image 176 are analyzed to determine strain exerted on the lateral section 162 by the athlete 122.

With reference to FIGS. 4A, 5, and 6, it should be understood that the cameras 110 (shown in FIGS. 1 and 2) may take additional images (not shown) of the reference shoe 124 directed toward the front section 164, the rear section 166, and/or the medial section 168 (shown in FIG. 1) as the athlete 122 moves along the track 106. The sampling rate at which the cameras 110 take these images is relatively fast (e.g., in a range between 200 samples per second and 2500 samples per second). In some instances, these additional images may be taken at the first time t₁ and/or the second time t₂. In some instances, these additional images may be taken at times differing from the first time t₁ and/or the second time t₂. It should be further understood that these additional images may be analyzed in the same manner as the calibration image 172, the first image 174, and/or the second image 176 to determine strain exerted on the front section 164, the rear section 166, and/or the medial section 168 by the athlete 122.

With reference to FIGS. 4A, 5, and 6, the plurality of reference marks 170 define a plurality of regions 178 between neighboring reference marks 170. For example, a first reference mark 180 neighbors a second reference mark 182. Thus, the plurality of reference marks 170 includes a plurality of neighboring reference mark sets 184. For example, the first reference mark 180 and the second reference mark 182 form one of the plurality of neighboring reference mark sets 184. In other words, each region 178 is defined by one of the plurality of neighboring reference mark sets 184. It should be understood that each reference mark 170 may be part of multiple neighboring reference mark sets 184.

With reference to FIG. 4A, at the calibration time t₀, the first reference mark 180 is separated from the second reference mark 182 by a reference distance D₀ across the region 178. With reference to FIG. 5, at the first time t₁, the first reference mark 180 is separated from the second reference mark 182 by a first distance D₁ across the region 178. With reference to FIG. 6, at the second time t₂, the first reference mark 180 is separated from the second reference mark 182 by a second distance D₂ across the region 178. In the illustrated examples of FIGS. 4A, 5, and 6, D₁ is longer than D₀ and D₂ is longer than D₁. Thus, in the examples of FIGS. 4A and 5, the foot of the athlete 122 moves laterally outwardly relative to the sole 158 against the region 178 to stretch the upper 154 from the reference distance D₀ (shown in FIG. 4A) to the first distance D₁. In other words, the region 178 stretches by the difference between the reference distance D₀ and the first distance D₁ under outward lateral pressure exerted by the foot of the athlete 122. It should be understood that, depending on the movements of the athlete 122 (shown in FIGS. 1, 2, and 4), D₁ may be shorter than or equal to D₀. When D₁ is shorter than D₀, the region 178 is compressed. When D₁ is equal to D₀, no net forces are acting on the region 178.

Further, in the example of FIGS. 5 and 6, during the time period from the first time t₁ to the second time t₂, the foot of the athlete 122 moves laterally outwardly relative to the sole 158 against the region 178 to stretch the upper 154 from the first distance D₁ (shown in FIG. 5) to the second distance D₂. In other words, the region 178 stretches by the difference between the first distance D₁ and the second distance D₂ under outward lateral pressure exerted by the foot of the athlete 122. It should be understood that, depending on the movements of the athlete 122 (shown in FIGS. 1, 2, and 4), D₂ may be shorter than or equal to D₁. When D₂ is shorter than D₁, the region 178 is compressed during the time period from the first time t₁ to the second time t₂. When D₂ is equal to D₁, no net forces have acted on the region 178 during the time period from the first time t₁ to the second time t₂.

With reference to FIGS. 1, 2, and 3, in operation, the controller 114 receives the calibration image 172 (shown in FIG. 4A), the first image 174 (shown in FIG. 5), and/or the second image 176 (shown in FIG. 6) from the cameras 110. In other words, in operation, the controller 114 receives the calibration image 172 (shown in FIG. 4A) and one or more of the time-separated pair of images directed to the lateral section 162 (shown in FIGS. 4, 5, and 6) from the cameras 110. It should be understood that the controller 114 additionally receives calibration images and time-separated pairs of images directed to the front section 164 (shown in FIGS. 4, 5, and 6), the rear section 166 (shown in FIGS. 4, 5, and 6), and the medial section 168 from the cameras 110 (shown in FIG. 1). Further in operation, the controller 114 analyzes the received calibration images (e.g., the calibration image 172) and time-separated pairs of images (e.g., the first image 174 and the second image 176) to generate a strain map 186 (shown in FIG. 7), as will be explained in greater detail below.

With reference to FIG. 7, the strain map 186 includes a legend 188, an upper guide 190, a tongue guide 192, strain indicators 196, and reinforcement thickness values 198. The strain indicators 196 are distributed across the upper guide 190 and the tongue guide 192 according to the analysis of the first image 174 and the second image 176. The strain indicators 196 are graphical representations of mechanical strain e experienced by the upper 154 (shown in FIG. 4) and/or the tongue 156 while the athlete 122 (shown in FIGS. 1, 2, and 4) moved along the track 106. The legend 188 correlates the graphical representation of the strain indicators 196 to the reinforcement thickness values 198. More specifically, strain e is described by Equation 1, below:

$\begin{matrix} {e = \frac{D_{1} - D_{0}}{D_{0}}} & {{Equation}\mspace{14mu} 1} \end{matrix}$

Thus, in Equation 1, e is the ratio of the change in length between the reference distance D₀ (shown in FIG. 4A) and the first distance D₁ (shown in FIG. 5) as compared to the reference distance D₀. It should be appreciated that because D₀ and D₁ both have units of length (e.g., millimeters and/or inches), strain e is unitless. Strain e is often described in terms of percentage.

In some instances, strain e is described by Equation 2, below:

$\begin{matrix} {e = \frac{D_{2} - D_{1}}{D_{1}}} & {{Equation}\mspace{14mu} 2} \end{matrix}$

Thus, in Equation 2, e is the ratio of the change in length between the first distance D₁ (shown in FIG. 5) and the second distance D₂ (shown in FIG. 6) as compared to the first distance D₁.

With reference to FIG. 8, shoe components 200 include a first example upper blank 204 and a tongue blank 206. The upper blank 204 includes a first substrate 210, which has a seam flange 212 and defines lace holes 214. The upper blank 204 is a pre-made structure ready for 3D printing. In some embodiments, the first substrate 210 is formed of an elastomeric textile. The upper blank further includes a first plurality of reinforcements 216 applied to the first substrate 210 by the 3D printer 118 (shown in FIGS. 1 and 2) according to the strain map 186 (shown in FIG. 7), as will be explained in greater detail below. The tongue blank 206 includes a second substrate 222, which defines a lace holder 224. The tongue blank 206 is also a pre-made structure ready for 3D printing. The tongue blank 206 further includes a second plurality of reinforcements 226 applied to the second substrate 222 by the 3D printer 118 according to the strain map 186, as will also be explained in greater detail below. In some embodiments, the first plurality of reinforcements 216 and/or the second plurality of reinforcements 226 are resilient and/or are composed of an elastomer. In the example of FIG. 8, the first plurality of reinforcements 216 and the second plurality of reinforcements 218 are shaped as a plurality of dashes. With reference to FIG. 9, in some embodiments, the reinforcement data 152 is organized as a look-up table. The reinforcement data 152 includes strain value ranges 234 and the reinforcement thickness values 198. The reinforcement data 152 correlates the strain value ranges 234 to the reinforcement thickness values 198.

With reference to FIG. 3, in operation, the image receiver 140 receives the calibration image 172 (shown in FIG. 4A), the first image 174 (shown in FIG. 5), and the second image 176 (shown in FIG. 6) from the cameras 110. In some embodiments, the cameras 110 send image data to the controller 114 as the image data is produced. Thus, in some embodiments, the controller 114 receives the second image 176 after the first image 174. Further, in some embodiments, the controller 114 receives the first image 174 after the calibration image 172. In some embodiments, the controller 114 receives the calibration image 172, the first image 174, and the second image 176 generally simultaneously.

With reference to FIG. 3, in operation, the reference detector 142 detects the plurality of reference marks 170 (shown in FIGS. 4A, 5, and 6) in the calibration image 172, the first image 174, and/or in the second image 176. More specifically, the reference detector 142 detects neighboring reference mark sets 184 visible in the calibration image 172, the first image 174 and/or in the second image 176. For example, the reference detector 142 detects the first reference mark 180 and the second reference mark 182. The reference detector 142 detects the plurality of reference marks 170 (e.g., the first reference mark 180 and the second reference mark 182) via one or more of edge detection, contrast differentiation, pattern recognition, etc.

With reference to FIG. 3, in operation, the distance determiner 144 determines distances between reference marks 170 in neighboring reference mark sets 184 in the first image 174 and in the second image 176. In other words, the distance determiner 144 determines distances across the regions 178 in the first image 174 and in the second image 176. For example, the distance determiner 144 determines the reference distance D₀ between the first reference mark 180 and the second reference mark 182 in the calibration image 172. Additionally, the distance determiner 144 determines the first distance D₁ between the first reference mark 180 and the second reference mark 182 in the first image 174. Further, for example, the distance determiner 144 determines the second distance D₂ between the first reference mark 180 and the second reference mark 182 in the second image 176.

With reference to FIG. 3, in operation, the distance comparator 146 compares the distances between reference marks 170 in neighboring reference mark sets 184 determined from the first image 174 and the second image 176. In other words, the distance comparator 146 compares the distances across the regions 178 found from the calibration image 172, the first image 174 and/or the second image 176. For example, the distance comparator 146 compares the reference distance D₀ (shown in FIG. 4A) to the first distance D₁ (shown in FIG. 5). As another example, the distance comparator 146 compares the reference distance D₀ (shown in FIG. 4A) to the second distance D₂ (shown in FIG. 6). In a further example, the distance comparator 146 compares the first distance D₁ to the second distance D₂. Further, the distance comparator 146 determines differences between the distances determined from the calibration image 172, the first image 174, and/or the second image 176. In other words, the distance comparator 146 determines distance differences corresponding to each neighboring reference mark set 184. For example, the distance comparator 146 determines a difference between the reference distance D₀ and the first distance D₁. As another example, the distance comparator 146 determines a difference between the reference distance D₀ and the second distance D₂. In a further example, the distance comparator 146 determines a difference between the first distance D₁ and the second distance D₂.

With reference to FIG. 3, in operation, the strain determiner 148 determines strain values e corresponding to each region 178 based on the determined distance differences and the distances found in the first image 174 according to Equation 1 and/or Equation 2, above. For example, the strain determiner 148 determines a strain value e from the difference between the reference distance D₀ and the first distance D₁ as compared to the reference distance D₀ according to Equation 1. In another example, the strain determiner 148 determines a strain value e from the difference between the first distance D₁ and the second distance D₂ as compared to the first distance D₁ according to Equation 2.

With reference to FIG. 3, it should be understood that the image receiver 140, the reference detector 142, the distance determiner 144, the distance comparator 146, and the strain determiner 148 receive, process, and analyze the time-separated pairs of images directed to the front section 164 (shown in FIGS. 4, 5, and 6), the rear section 166 (shown in FIGS. 4, 5, and 6), and/or the medial section 168 (shown in FIG. 1) in the same manner as the calibration image 172, the first image 174, and the second image 176. Thus, the controller 114 generates strain values e for the lateral section 162, the front section 164, the rear section 166, and/or the medial section 168. In other words, the controller 114 generates strain values e for some or all portions of the reference shoe 124 using image data from the cameras 110 (shown in FIG. 1).

With reference to FIG. 3, in operation, the map compiler 150 compiles and graphically represents the strain values e to generate the strain map 186. More specifically, the map compiler 150 positions the strain indicators 196 on the strain map 186 corresponding to the regions 178 (shown in FIGS. 5 and 6). Additionally, the map compiler 150 accesses the reinforcement data 152 (shown in FIGS. 3 and 9) and assigns one of reinforcement thickness values 198 to each strain indicator 196 according to the corresponding strain values e for each region 178. Further, the map compiler 150 codes the strain indicators 196 according to the corresponding strain values e and/or reinforcement thickness values 198 (e.g., by color, numeral tags, vector arrows, thickness, pattern, etc.). Thus, the strain indicators 196 are mapped onto the upper guide 190 and the tongue guide 192 according to the strain values e for each region 178. Continuing in operation, the map compiler 150 sends the generated strain map 186 to the 3D printer 118.

With reference to FIG. 8, the 3D printer 118 (shown in FIG. 3) produces the shoe components 200. More specifically, the 3D printer 118 extrudes and/or deposits the first plurality of reinforcements 216 directly onto the first substrate 210 according to the positions and reinforcement thickness values 198 indicated by the strain map 186 to produce a customized upper 238. Additionally, the 3D printer 118 extrudes and/or deposits the second plurality of reinforcements 226 directly onto the second substrate 222 according to the positions and reinforcement thickness values 198 indicated by the strain map 186 to produce a customized tongue 240. In some embodiments, the first plurality of reinforcements 216 and/or the second plurality of reinforcements 226 are composed of an elastomer. Thus, the first substrate 210 is variably reinforced and/or stiffened by the first plurality of reinforcements 216. Similarly, the second substrate 222 is variably reinforced and/or stiffened by the second plurality of reinforcements 226. Thus, the shoe components 200 are customized to the athlete 122. With reference to FIG. 11, once the first plurality of reinforcements 216 and the second plurality of reinforcements 226 are cured (e.g., by the 3D printer 118), the shoe components 200 may be utilized with a sole 242 and laces 244 to construct a customized shoe 248 specifically for the athlete 122. More specifically, the customized upper 238 may be connected to the customized tongue 240 (e.g., stitched, adhered, welded, etc.) and further connected to the sole 242.

With reference to FIG. 12, a second example upper blank 304 includes the first substrate 210 and is a pre-made structure ready for 3D printing. The upper blank 304 further includes a plurality of reinforcements 316 applied to the first substrate 210 by the 3D printer 118 (shown in FIGS. 1 and 2) according to the strain map 186 (shown in FIG. 7), in the same manner as with the first example upper blank 204 and the example tongue 206 (shown in FIG. 8). In some embodiments, the plurality of reinforcements 316 are resilient and/or are composed of an elastomer. In the example of FIG. 12, the plurality of reinforcements 316 are shaped as a plurality of lines.

With reference to FIG. 13, a third example upper blank 404 includes the first substrate 210 and is a pre-made structure ready for 3D printing. The upper blank 404 further includes a plurality of reinforcements 416 applied to the first substrate 210 by the 3D printer 118 (shown in FIGS. 1 and 2) according to the strain map 186 (shown in FIG. 7), in the same manner as with the first example upper blank 204 and the example tongue 206 (shown in FIG. 8). In some embodiments, the plurality of reinforcements 416 are resilient and/or are composed of an elastomer. In the example of FIG. 13, the plurality of reinforcements 416 are shaped as a plurality of lines along which pointed dots are disposed.

With reference to FIG. 14, a fourth example upper blank 504 includes the first substrate 210 and is a pre-made structure ready for 3D printing. The upper blank 504 further includes a plurality of reinforcements 516 applied to the first substrate 210 by the 3D printer 118 (shown in FIGS. 1 and 2) according to the strain map 186 (shown in FIG. 7), in the same manner as with the first example upper blank 204 and the example tongue 206 (shown in FIG. 8). In some embodiments, the plurality of reinforcements 516 are resilient and/or are composed of an elastomer. In the example of FIG. 14, the plurality of reinforcements 516 are shaped as a plurality of pointed dots.

With reference to FIG. 15, a fifth example upper blank 604 includes the first substrate 210 and is a pre-made structure ready for 3D printing. The upper blank 604 further includes a plurality of reinforcements 616 applied to the first substrate 210 by the 3D printer 118 (shown in FIGS. 1 and 2) according to the strain map 186 (shown in FIG. 7), in the same manner as with the first example upper blank 204 and the example tongue 206 (shown in FIG. 8). In some embodiments, the plurality of reinforcements 616 are resilient and/or are composed of an elastomer. In the example of FIG. 15, the plurality of reinforcements 616 are shaped as a plurality of lines along which hexagons are disposed.

With reference to FIG. 16, a sixth example upper blank 704 includes the first substrate 210 and is a pre-made structure ready for 3D printing. The upper blank 704 further includes a plurality of reinforcements 716 applied to the first substrate 210 by the 3D printer 118 (shown in FIGS. 1 and 2) according to the strain map 186 (shown in FIG. 7), in the same manner as with the first example upper blank 204 and the example tongue 206 (shown in FIG. 8). In some embodiments, the plurality of reinforcements 716 are resilient and/or are composed of an elastomer. In the example of FIG. 16, the plurality of reinforcements 716 are shaped as a plurality of tear drops.

With reference to FIG. 17, a seventh example upper blank 804 includes the first substrate 210 and is a pre-made structure ready for 3D printing. The upper blank 804 further includes a plurality of reinforcements 816 applied to the first substrate 210 by the 3D printer 118 (shown in FIGS. 1 and 2) according to the strain map 186 (shown in FIG. 7), in the same manner as with the first example upper blank 204 and the example tongue 206 (shown in FIG. 8). In some embodiments, the plurality of reinforcements 816 are resilient and/or are composed of an elastomer. In the example of FIG. 17, the plurality of reinforcements 316 are shaped as a plurality of rectangles.

A flowchart representative of a first example method 1000 that may be performed to produce variably resilient elastomers is depicted in FIG. 10. The flowchart of FIG. 10 is representative of machine readable instructions that are stored in memory (such as the memory 134 of FIGS. 1-3) and include one or more programs which, when executed by a processor (such as the processor 132 of FIGS. 1-3), cause the controller 114 to operate the example system 100 of FIGS. 1 and 2. While the example program is described with reference to the flowchart illustrated in FIG. 10 many other methods of operating the example system 100 may alternatively be used. For example, the order of execution of the blocks may be rearranged, changed, eliminated, and/or combined to perform the method 1000. Further, because the method 1000 is disclosed in connection with the components of FIGS. 1 and 2, some functions of those components will not be described in detail below.

Initially, at block 1002, the controller 114 receives images from the cameras 110. More specifically, the image receiver 140 receives the calibration image 172 taken at the calibration time t₀ and the first image 174 taken at the first time t₁. In some embodiments, the image receiver 140 receives the first image 174 and the second image 176 subsequently taken at the second time t₂. In some embodiments, image receiver 140 receives the calibration image 172 taken at the calibration time t₀ and the second image 176.

At block 1004, the controller 114 detects reference marks 170 in the images (e.g., the calibration image 172, the first image 174, the second image 176, etc.). More specifically, the reference detector 142 finds neighboring reference mark sets 184 and their corresponding regions 178.

At block 1006, the controller 114 determines distances across the regions 178. More specifically, the distance determiner 144 finds lengths between reference marks 170 of neighboring reference mark sets 184 in the images.

At block 1008, the controller 114 compares distances across the regions 178 between the images. More specifically, the distance comparator 146 determines length differences between the distances from the respective images corresponding to each region 178.

At block 1010, the controller 114 determines strain values e for each region 178. More specifically, the strain determiner 148 computes strain values e corresponding to each region 178 based on the determined length differences and the distances from the images.

At block 1012, the controller 114 compiles the strain map 186. More specifically, the map compiler 150 positions strain indicators 196 on the upper guide 190 and the tongue guide 192 corresponding to each of the regions 178. The map compiler 150 assigns reinforcement thickness values 198 to each of the strain indicators 196 according to the reinforcement data 152 and the determined strain values e corresponding to the regions 178.

At block 1014, the 3D printer 118 additively manufactures the shoe components 200. More specifically, the 3D printer 118 deposits and/or extrudes the first plurality of reinforcements 216 onto the first substrate 210 and the second plurality of reinforcements 226 onto the second substrate 222 according to the strain map 186. The method 1000 then returns to block 1002.

From the foregoing, it will be appreciated that the above example system 100 includes cameras and a controller to measure strain in an athlete's shoes and generate a strain map of the shoes. The system 100 also includes a 3D printer to produce reinforced shoe components according to the strain map. Thus, the reinforced shoe components are customized to the athlete's feet. Because the shoe components are reinforced, the shoe components may be more durable as to existing athletic shoe components. Thus, the above-disclosed example system 100 conserves resources as compared to existing athletic shoe production systems.

While various spatial and directional terms, such as top, bottom, lower, mid, lateral, horizontal, vertical, front and the like may be used to describe embodiments of the present disclosure, it is understood that such terms are merely used with respect to the orientations shown in the drawings. The orientations may be inverted, rotated, or otherwise changed, such that an upper portion is a lower portion, and vice versa, horizontal becomes vertical, and the like.

Variations and modifications of the foregoing are within the scope of the present disclosure. It is understood that the embodiments disclosed and defined herein extend to all alternative combinations of two or more of the individual features mentioned or evident from the text and/or drawings. All of these different combinations constitute various alternative aspects of the present disclosure. The claims are to be construed to include alternative embodiments to the extent permitted by the prior art.

To the extent used in the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Moreover, to the extent used in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects. Further, the limitations of the following claims are not written in means-plus-function format and are not intended to be interpreted based on 35 U.S.C. § 112(f), unless and until such claim limitations expressly use the phrase “means for” followed by a statement of function void of further structure.

Various features of the disclosure are set forth in the following claims. 

What is claimed is:
 1. A system to measure strain in an article, comprising: a camera to capture a plurality of images of the article; and a processor and memory in selective communication with the camera and configured to determine strain in a region of the article based on a plurality of reference marks shown in the plurality of images.
 2. The system of claim 1, wherein the processor and memory are further configured to compare positions of the plurality of reference marks relative to one another.
 3. The system of claim 1, wherein: the plurality of images includes a first image and a second image, the plurality of reference marks includes a first reference mark and a second reference mark, the first reference mark is shown in the first image and in the second image, the second reference mark is shown in the first image and in the second image, and the processor and memory are further configured to determine a first distance between the first reference mark and the second reference mark shown in the first image, and determine a second distance between the first reference mark and the second reference mark shown in the second image.
 4. The system of claim 3, wherein the processor and memory are further configured to determine a difference between the first distance and the second distance.
 5. The system of claim 4, wherein: the region is between the first reference mark and the second reference mark, and the processor and memory are further configured to determine the strain in the region based on the difference.
 6. The system of claim 1, wherein the processor and memory are further configured to detect the plurality of reference marks shown in the plurality of images.
 7. The system of claim 1, wherein: the plurality of images includes a first image and a second image, and the second image is captured after the first image.
 8. The system of claim 1, wherein the processor and memory are further configured to generate a strain map.
 9. The system of claim 8, wherein the strain map includes a strain value mapped via one or more of color coding, vector arrows, and numeral tags.
 10. The system of claim 8, wherein the strain map include a strain indicator mapped according to the strain in the region.
 11. The system of claim 1, wherein the camera is a first camera and further including a second camera in selective communication with the processor and the memory.
 12. The system of claim 11, wherein the first camera and the second camera are coupled together as a stereoscopic camera.
 13. The system of claim 12, wherein the plurality of images are stereoscopic images.
 14. The system of claim 11, wherein: the region is a first region, the plurality of images is a first plurality of images, the plurality of reference marks is a first plurality of reference marks, the second camera captures a second plurality of images, and the processor and memory are further configured to determine strain in a second region of the article based on a second plurality of reference marks shown in the second plurality of images.
 15. The system of claim 14, wherein: the first camera is directed to a first side of the article, and the second camera is directed to a second side of the article.
 16. A method to measure strain in an article, comprising: capturing, with a camera, a plurality of images of the article; and determining, with a processor, strain in a region of the article based on a plurality of reference marks shown in the plurality of images.
 17. The method of claim 16, wherein: the plurality of images includes a first image and a second image, the plurality of reference marks includes a first reference mark and a second reference mark, the first reference mark is shown in the first image and in the second image, the second reference mark is shown in the first image and in the second image, and determining strain in the region includes determining a first distance between the first reference mark and the second reference mark shown in the first image, and determining a second distance between the first reference mark and the second reference mark shown in the second image.
 18. The method of claim 17, wherein determining strain in the region includes determining a difference between the first distance and the second distance, and determining a value based on the difference and the first distance.
 19. A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to: determine strain in a region of an article based on a plurality of reference marks shown in a plurality of images.
 20. The non-transitory computer readable medium of claim 19, wherein: the plurality of images includes a first image and a second image, the plurality of reference marks includes a first reference mark and a second reference mark, the first reference mark is shown in the first image and in the second image, the second reference mark is shown in the first image and in the second image, and the instructions further cause the processor to determine a first distance between the first reference mark and the second reference mark shown in the first image, and determine a second distance between the first reference mark and the second reference mark shown in the second image.
 21. A system to produce a customized component, comprising: a camera to capture images of an article; a processor and memory in selective communication with the camera and configured to determine a strain value in a region of the article based on the images, and generate a strain map based on the strain value; and a 3D printer in selective communication with the processor and memory and configured to apply reinforcement to a substrate according to the strain map. 